Principal Vision Developer at The Nuclear Company

Seattle, Washington, United States -

Full Time

Start Date

Immediate

Expiry Date

27 Feb, 26

Salary

228000.0

Posted On

29 Nov, 25

Experience

10 year(s) or above

Remote Job

Yes

Telecommute

Yes

Sponsor Visa

Skills

Computer Vision, Machine Learning, AI Development, Image Processing, Camera Systems Integration, Real-Time Video Analytics, Deep Learning, Python, C++, Data Pipelines, Safety Monitoring, Quality Control, Construction Processes, BIM Models, Robotic Vision, Automation

Industry

Nuclear Electric Power Generation

Description

The Nuclear Company is the fastest growing startup in the nuclear and energy space creating a never before seen fleet-scale approach to building nuclear reactors. Through its design-once, build-many approach and coalition building across communities, regulators, and financial stakeholders, The Nuclear Company is committed to delivering safe and reliable electricity at the lowest cost, while catalyzing the nuclear industry toward rapid development in America and globally. Principal Vision Developer Position Overview The Principal Vision Developer is a senior technical leadership role responsible for designing, developing, and deploying advanced computer vision and AI-powered visual systems that transform nuclear construction, safety monitoring, and quality control. This position requires deep expertise in machine learning, image processing, camera systems integration, and real-time video analytics to enable automated progress tracking, safety compliance monitoring, and intelligent inspection systems for Nuclear OS. You'll work at the intersection of artificial intelligence and nuclear infrastructure, helping to automate visual inspection, detect anomalies, and ensure construction quality through cutting-edge computer vision technology. Key Responsibilities Computer Vision System Development Design and develop AI-powered computer vision systems for automated construction progress monitoring, comparing current site images to BIM models to determine completion percentages Build real-time video analytics systems that analyze camera feeds and drone imagery to detect construction issues, missing components, and deviations from design Develop automated inspection systems using AI and computer vision to verify construction quality and detect deviations Create computer vision algorithms for anomaly detection, defect identification, and automated image analysis from drone and camera feeds Implement 3D reconstruction from image sequences and point clouds for digital twin development Camera Systems Integration & Detection Design and deploy multi-camera networks across construction sites for comprehensive visual coverage Integrate AI-enabled cameras into IoT sensor networks for real-time data collection and analysis Implement camera calibration systems for accurate geometric measurements and 3D reconstruction Develop multi-camera synchronization for stereo vision and 360-degree coverage Build camera management systems for configuration, monitoring, and maintenance of distributed camera networks Integrate various camera types including fixed surveillance cameras, PTZ cameras, thermal/infrared cameras, and mobile drone cameras Design detection pipelines that process video streams from multiple cameras simultaneously Implement intelligent camera placement strategies to optimize coverage and minimize blind spots Create camera health monitoring systems to detect and alert on camera failures or degraded performance Develop bandwidth optimization for efficient video streaming from large camera networks Safety & Compliance Monitoring Develop AI safety enforcement systems that analyze camera feeds in real-time to detect PPE compliance (helmets, vests, safety glasses) Build perimeter monitoring systems that detect unauthorized personnel or equipment breaches during critical operations like heavy lifts Create automated alert systems that log safety violations and notify supervisors immediately when non-compliance is detected Develop hazard detection models that identify unsafe conditions, obstructions, or potential safety risks in construction zones Implement worker tracking systems using camera-based detection for safety monitoring and emergency response Build tailgating detection systems that identify when multiple people enter on a single badge swipe Progress Tracking & Quality Control Build automated progress assessment systems using computer vision to track work package completion Develop material classification algorithms that automatically identify installed components and materials from construction site images Create surveillance video analysis systems to detect and track work packages' components automatically Implement activity recognition models (using YOLO, CNNs) to monitor construction activities and assess task completion times Build defect detection systems for automated quality inspection of welds, concrete pours, and structural installations Develop visual comparison tools that overlay as-built conditions against design models to identify discrepancies Create truck and material arrival detection using camera-based AI at jobsite entrance gates Machine Learning & AI Model Development Train deep learning models (CNNs, transformers, YOLO, R-CNN) for object detection, segmentation, and classification in construction environments Develop custom datasets from drone imagery, site cameras, and inspection photos with proper labeling and annotation Implement transfer learning to adapt pre-trained models for nuclear construction-specific applications Create ensemble models that combine multiple vision techniques for robust performance Optimize models for real-time inference on edge devices and GPU-accelerated servers Implement continuous learning pipelines that improve model accuracy over time with new data Build convolutional neural network-based detection systems for automated identification and classification Integration & Deployment Integrate computer vision systems with Nuclear OS platform for seamless data flow and automated reporting Deploy vision models on edge devices, cloud infrastructure, and hybrid architecture Connect to IoT camera networks and drone feeds for real-time image acquisition Build APIs and microservices for vision system integration with other Nuclear OS modules Implement data pipelines for image ingestion, preprocessing, inference, and result storage Create visualization dashboards showing real-time progress metrics, safety alerts, and quality issues Integrate with access control systems for enhanced security monitoring Design isolated security networks for camera systems in sensitive areas Robotic Vision & Automation Develop computer vision systems for robotic perception and autonomous navigation Integrate vision systems with robotic inspection and quality control platforms Build visual servoing systems for robot guidance and manipulation tasks Develop 3D pose estimation for robotic pick-and-place operations Create visual SLAM systems for autonomous robot navigation in construction sites Advanced Vision Applications Implement photogrammetry pipelines for 3D reconstruction from drone and camera imagery Develop infrared and thermal imaging analysis for equipment monitoring and anomaly detection Build optical character recognition (OCR) systems for automated document processing and equipment labeling Create facial recognition systems for access control and personnel tracking (where permitted) Develop appearance-based search for security and incident investigation across multiple camera feeds Implement vehicle and individual tracking across facility camera networks for security analysis Technical Leadership & Innovation Provide expert guidance on computer vision architecture, camera systems, algorithms, and best practices Lead cross-functional teams involving data scientists, software engineers, network engineers, and domain experts Evaluate emerging vision technologies including foundation models, vision transformers, and multimodal AI Establish development standards for vision system deployment in nuclear environments Mentor junior developers on machine learning, computer vision, and AI techniques Represent TNC in industry forums on AI and computer vision applications Drive innovation in automated construction monitoring and intelligent inspection systems Required Qualifications Education & Experience Bachelor's degree in Computer Science, Electrical Engineering, Computer Engineering, or related field (Master's or Ph.D. preferred) 12+ years of experience in computer vision, machine learning, or AI development 5+ years in a senior or lead role with demonstrated technical leadership Experience in industrial, construction, or manufacturing applications preferred Technical Skills - Computer Vision Expert proficiency in computer vision libraries (OpenCV, scikit-image, PIL/Pillow) Deep understanding of classical CV techniques (edge detection, feature extraction, optical flow, SLAM) Experience with 3D computer vision (stereo vision, structure from motion, photogrammetry) Knowledge of image processing techniques (filtering, segmentation, morphological operations) Proficiency in video analytics and real-time processing Understanding of camera calibration, lens distortion correction, and geometric transformations Technical Skills - Camera Systems & Hardware Strong experience with camera integration, configuration, and management Knowledge of camera protocols (ONVIF, RTSP, HTTP streaming, GigE Vision) Understanding of camera specifications (resolution, frame rate, dynamic range, sensor types) Experience with various camera types (IP cameras, thermal cameras, PTZ cameras, industrial cameras) Proficiency in multi-camera synchronization and calibration Knowledge of video compression standards (H.264, H.265, MJPEG) Understanding of network bandwidth requirements and optimization for video streaming Familiarity with camera mounting, positioning, and field-of-view calculations Technical Skills - Machine Learning & Deep Learning Expert knowledge of deep learning frameworks (PyTorch, TensorFlow, Keras) Strong experience with CNNs, vision transformers, and modern architectures (ResNet, YOLO, Mask R-CNN, ViT) Proficiency in object detection, semantic segmentation, and instance segmentation Experience with model training, hyperparameter tuning, and optimization Knowledge of transfer learning, fine-tuning, and domain adaptation Understanding of data augmentation, regularization, and model evaluation techniques Technical Skills - Programming & Development Expert programming skills in Python (primary) and C++ (for performance-critical code) Proficiency in GPU programming (CUDA, cuDNN) for accelerated inference Experience with MLOps tools (MLflow, Weights & Biases, TensorBoard) Knowledge of containerization (Docker, Kubernetes) for model deployment Familiarity with cloud platforms (AWS SageMaker, Azure ML, Google Cloud AI) Understanding of REST APIs, microservices, and distributed systems Technical Skills - Data & Infrastructure Experience with large-scale image datasets and data annotation tools (Labelbox, CVAT, Label Studio) Knowledge of data pipelines, ETL processes, and data versioning (DVC) Proficiency in database systems for image metadata and results storage Understanding of edge computing and model optimization (TensorRT, ONNX, quantization) Familiarity with streaming video processing and real-time analytics Experience with video management systems (VMS) and network video recorders (NVR) Domain Knowledge Understanding of construction processes, quality control, and safety requirements Knowledge of BIM models, CAD data, and 3D visualization Familiarity with industrial inspection and automated monitoring systems Experience with regulatory compliance and documentation requirements Understanding of nuclear facility operations and safety protocols (preferred) Knowledge of security systems and surveillance best practices Soft Skills Excellent problem-solving abilities with creative approach to vision challenges Strong communication skills to explain complex AI concepts to diverse stakeholders Project management experience delivering production vision systems Ability to work collaboratively across engineering, operations, security, and safety teams Strategic thinking with focus on scalable, maintainable solutions Attention to detail for accuracy-critical applications Preferred Qualifications Ph.D. in Computer Vision, Machine Learning, or related field Publications in top-tier computer vision conferences (CVPR, ICCV, ECCV) Experience in nuclear, energy, or highly regulated industries Background in robotics, autonomous systems, or industrial automation Knowledge of 3D sensors (LiDAR, depth cameras, structured light) Experience with multi-camera systems and camera networks Familiarity with real-time operating systems and embedded vision Certifications in AI/ML (AWS ML Specialty, Google ML Engineer, etc.) Contributions to open-source computer vision projects Experience with video surveillance systems and security analytics Knowledge of lighting design for optimal camera performance Work Environment Hybrid work environment with office-based development and field testing Nuclear construction sites requiring safety training and PPE Collaboration with construction crews, safety personnel, engineers, and data scientists Occasional travel to multiple project sites for camera deployment and system integration Fast-paced environment with evolving AI technologies Why This Role Matters Computer vision is transforming nuclear construction by enabling automated progress tracking, real-time safety monitoring, and intelligent quality control through integrated camera systems. By developing AI-powered visual systems with comprehensive camera networks, you'll help reduce construction errors, improve safety compliance, and accelerate project timelines. Research shows that computer vision can automate progress assessment with 80%+ accuracy, dramatically reducing manual inspection time and catching issues before they become expensive problems. This role is critical to TNC's vision of fleet-scale nuclear deployment through AI-driven automation and intelligent construction management powered by integrated camera detection systems. This position offers the opportunity to apply state-of-the-art computer vision, AI technologies, and camera integration to one of the most important challenges of our time—building clean, carbon-free nuclear energy infrastructure at scale through intelligent automation and comprehensive visual monitoring. Benefits Competitive compensation packages 401k with company match Medical, dental, vision plans Generous vacation policy, plus holidays Estimated Starting Salary Range The estimated starting salary range for this role is $198,000- $228,000 annually less applicable withholdings and deductions, paid on a bi-weekly basis. The actual salary offered may vary based on relevant factors as determined in the Company’s discretion, which may include experience, qualifications, tenure, skill set, availability of qualified candidates, geographic location, certifications held, and other criteria deemed pertinent to the particular role. EEO Statement The Nuclear Company is an equal opportunity employer committed to fostering an environment of inclusion in the workplace. We provide equal employment opportunities to all qualified applicants and employees without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, age, disability, veteran status, or any other protected characteristic. We prohibit discrimination in all aspects of employment, including hiring, promotion, demotion, transfer, compensation, and termination. Export Control Certain positions at The Nuclear Company may involve access to information and technology subject to export controls under U.S. law. Compliance with these export controls may result in The Nuclear Company limiting its consideration of certain applicants.

Responsibilities

The Principal Vision Developer is responsible for designing, developing, and deploying advanced computer vision and AI-powered visual systems for nuclear construction. This role involves automating visual inspection, detecting anomalies, and ensuring construction quality through cutting-edge technology.